电子学报 ›› 2016, Vol. 44 ›› Issue (4): 898-905.DOI: 10.3969/j.issn.0372-2112.2016.04.021

• 学术论文 • 上一篇    下一篇

基于多维特征分析的社交网络意见领袖挖掘

曹玖新, 陈高君, 吴江林, 刘波, 周涛, 胥帅, 朱子青   

  1. 1. 东南大学计算机科学与工程学院, 江苏南京 210096;
    2. 东南大学计算机网络和信息集成教育部重点实验室, 江苏南京 210096
  • 收稿日期:2014-10-16 修回日期:2015-06-12 出版日期:2016-04-25 发布日期:2016-04-25
  • 通讯作者: 曹玖新
  • 作者简介:陈高君 男,1988年生于河南漯河,东南大学硕士生,主要研究领域为社会计算;吴江林 男,1988年生于江苏南通市,东南大学硕士生,主要研究领域为社会计算.
  • 基金资助:

    国家863高技术研究发展计划(No.2013AA013503);东南大学计算机网络和信息集成教育部重点实验室基金(No.93k-9);国家973重点基础研究发展计划(No.2010CB328104);国家自然科学基金(No.61272531,No.61202449,No.61272054,No.61370207,No.61370208,No.61300024,No.61320106007,No.61472081);高等学校博士点学科专项科研基金(No.2011009213002);江苏省科技计划基金(No.SBY2014021039-10);江苏省网络与信息安全重点实验室基金(No.BM2003201)

Multi-Feature Based Opinion Leader Mining in Social Networks

CAO Jiu-xin, CHEN Gao-jun, WU Jiang-lin, LIU Bo, ZHOU Tao, XU Shuai, ZHU Zi-qing   

  1. 1. School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China;
    2. Key Laboratory of Computer Network and Information Integration (Ministry of Education), Southeast University, Nanjing, Jiangsu 210096, China
  • Received:2014-10-16 Revised:2015-06-12 Online:2016-04-25 Published:2016-04-25

摘要:

在社交网络中进行意见领袖的挖掘对信息传播与演化的深度分析、舆情监控和引导具有重要意义,本文综合结构特征、行为特征和用户的情感特征对意见领袖节点挖掘问题进行研究.本文首先对微博真实文本数据进行话题识别得到主题社区,在主题社区中基于用户节点之间的关注关系构建交互网络拓扑.然后分别从结构、行为和情感三个维度对用户的影响力进行度量.最后,分析用户在主题社区中的影响力分布与传播规律,提出意见领袖识别算法MFP(Multi-Feature PageRank).实验表明,该算法可有效地挖掘潜在的意见领袖节点,能够获得较高的支持率.

关键词: 社交网络, 话题, 情感分析, 意见领袖

Abstract:

Mining opinion leaders in social network is important for analysis of information dissemination and evolution of public opinion.This paper conducts the study on this problem considering structural features,behavior and emotional characteristics comprehensively.Firstly,we extract topics from micro-blogging texts,and get user communities according to the topic division,and an interactive network topology of topic community is built with the following relationships.Then,three kinds of user feature are gained from different aspect:network structure,user behavior and user sentiment.Finally,according to the analysis of users' influence distribution,opinion leaders mining algorithm MFP (Multi-Feature PageRank) is proposed.Experiments show that the algorithm can obtain the potential opinion leader nodes effectively,and have a good performance in support rate from other user nodes.

Key words: social network, topic, sentiment analysis, opinion leader

中图分类号: